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@t04glovern
Last active February 5, 2024 04:46
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Creates a sample Iceberg table in Athena allowing you to try out Iceberg easily. This script is geared towards people who are new to the AWS variety of Iceberg and keen to try some of the unique features of Iceberg.
#!/usr/bin/env python3
#
# pip install boto3
# ./lets-try-iceberg.py --bucket <bucket-name> --table <table-name> --compaction
#
# Creates the following files:
# - 1-athena-iceberg-create-table.sql - CREATE TABLE statement
# - 2-athena-create-temp-table.sql - CREATE EXTERNAL TABLE statement
# - 3-insert-into-iceberg-from-temp-table.sql - INSERT INTO statement
# - 4-cleanup-temp-table.sql - DROP TABLE statement
# - 5-cleanup-iceberg-table.sql - DROP TABLE statement
import argparse
import logging
import random
from datetime import datetime
from typing import Dict, Tuple, Union
import gzip
import json
import boto3
logging.basicConfig(level=logging.INFO)
aws_region: str = "us-west-2"
s3_client = boto3.client("s3", region_name=aws_region)
def generate_random_json(
id: str,
timestamp: datetime,
speed: float,
temperature: float,
location: Dict[str, float],
) -> Tuple[
Dict[str, Union[str, float, Dict[str, float]]], float, float, Dict[str, float]
]:
speed += random.randint(-5, 5)
temperature = round(temperature + random.uniform(-0.5, 0.5), 2)
location["lat"] += random.uniform(-0.0001, 0.0001)
location["lng"] += random.uniform(-0.0001, 0.0001)
return (
{
"id": id,
"timestamp": timestamp.isoformat(),
"speed": speed,
"temperature": temperature,
"location": location,
},
speed,
temperature,
location,
)
def generate_and_upload_jsonl(bucket_name: str, sample_count: int = 1000000):
gzip_filename = "samples.jsonl.gz"
s3_path = f"{bucket_name}/sample-data/{gzip_filename}"
with gzip.open(gzip_filename, "wt", encoding="UTF-8") as f:
for i in range(sample_count):
sample_data, _, _, _ = generate_random_json(
id=str(i % 5 + 1), # Cycling through IDs 1-5
timestamp=datetime.now(),
speed=random.randint(0, 100),
temperature=random.uniform(-20, 40),
location={
"lat": random.uniform(-90, 90),
"lng": random.uniform(-180, 180),
},
)
f.write(json.dumps(sample_data) + "\n")
with open(gzip_filename, "rb") as f:
s3_client.upload_fileobj(f, bucket_name, f"sample-data/{gzip_filename}")
logging.info(f"Uploaded {gzip_filename} to s3://{s3_path}")
def create_bucket(bucket_name: str):
try:
s3_client.head_bucket(Bucket=bucket_name)
except Exception as e:
logging.info(f"Bucket {bucket_name} does not exist, creating it...")
s3_client.create_bucket(
Bucket=bucket_name,
CreateBucketConfiguration={"LocationConstraint": aws_region},
)
else:
logging.info(f"Bucket {bucket_name} already exists, using it...")
def create_iceberg_query(bucket_name: str, table_name: str):
sql_content = f"""CREATE TABLE IF NOT EXISTS {table_name} (
`id` string,
`timestamp` timestamp,
`speed` int,
`temperature` float,
`location` struct < lat: float, lng: float >
)
PARTITIONED BY (
id
)
LOCATION 's3://{bucket_name}/'
TBLPROPERTIES (
'table_type'='ICEBERG',
'format'='parquet',
'write_compression'='zstd'
);
"""
with open("1-athena-iceberg-create-table.sql", "w") as sql_file:
sql_file.write(sql_content)
def create_athena_temp_table_sql(bucket_name: str, table_name: str):
sql_content = f"""CREATE EXTERNAL TABLE IF NOT EXISTS {table_name}_sample_data (
`id` string,
`timestamp` timestamp,
`speed` int,
`temperature` float,
`location` struct<lat:float, lng:float>
)
ROW FORMAT SERDE 'org.apache.hive.hcatalog.data.JsonSerDe'
WITH SERDEPROPERTIES ( "timestamp.formats"="yyyy-MM-dd'T'HH:mm:ss.SSSSSSZZ" )
LOCATION 's3://{bucket_name}/sample-data/'
"""
with open("2-athena-create-temp-table.sql", "w") as sql_file:
sql_file.write(sql_content)
def create_insert_from_temp_to_iceberg_sql(bucket_name: str, table_name: str):
sql_content = f"""INSERT INTO {table_name}
SELECT * FROM {table_name}_sample_data
"""
with open("3-insert-into-iceberg-from-temp-table.sql", "w") as sql_file:
sql_file.write(sql_content)
def create_cleanup_table_sql(table_name: str):
sql_content = f"""DROP TABLE IF EXISTS {table_name}_sample_data;
"""
with open("4-cleanup-temp-table.sql", "w") as sql_file:
sql_file.write(sql_content)
sql_content = f"""DROP TABLE IF EXISTS {table_name};
"""
with open("5-cleanup-iceberg-table.sql", "w") as sql_file:
sql_file.write(sql_content)
def create_iam_role_and_policy_iceberg_compaction(bucket_name: str, table_name: str):
iam_client = boto3.client("iam")
sts_client = boto3.client("sts")
account_id = sts_client.get_caller_identity()["Account"]
role_name = "lets-try-iceberg-compaction-role"
policy_name = "lets-try-iceberg-compaction-policy"
# Check for existing role
try:
iam_client.get_role(RoleName=role_name)
logging.info(f"IAM role {role_name} already exists")
except iam_client.exceptions.NoSuchEntityException:
# Create the role if it does not exist
assume_role_policy_document = json.dumps({
"Version": "2012-10-17",
"Statement": [{
"Effect": "Allow",
"Principal": {"Service": "glue.amazonaws.com"},
"Action": "sts:AssumeRole",
}]
})
iam_client.create_role(
RoleName=role_name, AssumeRolePolicyDocument=assume_role_policy_document
)
logging.info(f"Created IAM role {role_name}")
# Define the policy document
policy_document = {
"Version": "2012-10-17",
"Statement": [
# S3 permissions
{
"Effect": "Allow",
"Action": ["s3:PutObject", "s3:GetObject", "s3:DeleteObject"],
"Resource": [f"arn:aws:s3:::{bucket_name}/*"],
},
{
"Effect": "Allow",
"Action": ["s3:ListBucket"],
"Resource": [f"arn:aws:s3:::{bucket_name}"],
},
# Glue permissions
{
"Effect": "Allow",
"Action": ["glue:UpdateTable", "glue:GetTable"],
"Resource": [
f"arn:aws:glue:{aws_region}:{account_id}:table/default/{table_name}",
f"arn:aws:glue:{aws_region}:{account_id}:database/default",
f"arn:aws:glue:{aws_region}:{account_id}:catalog",
],
},
# Logs permissions
{
"Effect": "Allow",
"Action": [
"logs:CreateLogGroup",
"logs:CreateLogStream",
"logs:PutLogEvents",
],
"Resource": f"arn:aws:logs:{aws_region}:{account_id}:log-group:/aws-glue/iceberg-compaction/logs:*",
},
],
}
# Check for existing policy
try:
policy = iam_client.get_policy(PolicyArn=f"arn:aws:iam::{account_id}:policy/{policy_name}")
logging.info(f"IAM policy {policy_name} already exists, updating it...")
# Create a new version of the policy
policy_version = iam_client.create_policy_version(
PolicyArn=policy["Policy"]["Arn"],
PolicyDocument=json.dumps(policy_document),
SetAsDefault=True
)
# Optionally, clean up non-default versions of the policy
policy_versions = iam_client.list_policy_versions(PolicyArn=policy["Policy"]["Arn"])
for version in policy_versions["Versions"]:
if not version["IsDefaultVersion"]:
iam_client.delete_policy_version(
PolicyArn=policy["Policy"]["Arn"],
VersionId=version["VersionId"]
)
except iam_client.exceptions.NoSuchEntityException:
# Create the policy if it does not exist
policy = iam_client.create_policy(
PolicyName=policy_name, PolicyDocument=json.dumps(policy_document)
)
logging.info(f"Created IAM policy {policy_name}")
# Attach the policy to the role
iam_client.attach_role_policy(
RoleName=role_name, PolicyArn=policy["Policy"]["Arn"]
)
def main():
parser = argparse.ArgumentParser(description="Iceberg - Sample Table Creation")
parser.add_argument(
"--bucket",
type=str,
help="The S3 bucket name to store generated data. If not provided, a random bucket name will be generated.",
required=False,
)
parser.add_argument(
"--compaction",
action="store_true",
help="If provided, creates the compaction IAM role and policy.",
)
parser.add_argument(
"--table",
type=str,
help="The table name to use. If not provided, default to 'lets_try_iceberg'",
required=False,
default="lets_try_iceberg",
)
args = parser.parse_args()
bucket_name = args.bucket
if not bucket_name:
bucket_name = f"iceberg-sample-data-{random.randint(100000, 999999)}"
create_bucket(bucket_name)
table_name = args.table
create_iceberg_query(bucket_name, table_name)
generate_and_upload_jsonl(bucket_name)
create_athena_temp_table_sql(bucket_name, table_name)
create_insert_from_temp_to_iceberg_sql(bucket_name, table_name)
if args.compaction:
create_iam_role_and_policy_iceberg_compaction(bucket_name, table_name)
create_cleanup_table_sql(table_name)
if __name__ == "__main__":
main()
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